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Paradoxes of reservation-based intersection controls in traffic networks
Highlights We present three theoretical examples in which first-come-first-serve reservations are inferior to traffic signals. Traffic signals or merges/diverges perform better than first-come-first-serve reservations on some realistic networks. Despite favorable results in the current literature, more study on optimal reservation policies is needed.
Abstract Reservation-based intersection control is a revolutionary idea for using connected autonomous vehicle technologies to improve intersection controls. Vehicles individually request permission to follow precise paths through the intersection at specific times from an intersection manager agent. Previous studies have shown that reservations can reduce delays beyond optimized signals in many demand scenarios. The purpose of this paper is to demonstrate that signals can outperform reservations through theoretical and realistic examples. We present two examples that exploit the reservation protocol to prioritize vehicles on local roads over vehicles on arterials, increasing the total vehicle delay. A third theoretical example demonstrates that reservations can encourage selfish route choice leading to arbitrarily large queues. Next, we present two realistic networks taken from metropolitan planning organization data in which reservations perform worse than signals. We conclude with significantly positive results from comparing reservations and signals on the downtown Austin grid network using dynamic traffic assignment. Overall, these results indicate that network-based analyses are needed to detect adverse route choices before traffic signals can be replaced with reservation controls. In asymmetric intersections (e.g. local road-arterial intersections), reservation controls can cause several potential issues. However, in networks with more symmetric intersections such as a downtown grid, reservations have great potential to improve traffic.
Paradoxes of reservation-based intersection controls in traffic networks
Highlights We present three theoretical examples in which first-come-first-serve reservations are inferior to traffic signals. Traffic signals or merges/diverges perform better than first-come-first-serve reservations on some realistic networks. Despite favorable results in the current literature, more study on optimal reservation policies is needed.
Abstract Reservation-based intersection control is a revolutionary idea for using connected autonomous vehicle technologies to improve intersection controls. Vehicles individually request permission to follow precise paths through the intersection at specific times from an intersection manager agent. Previous studies have shown that reservations can reduce delays beyond optimized signals in many demand scenarios. The purpose of this paper is to demonstrate that signals can outperform reservations through theoretical and realistic examples. We present two examples that exploit the reservation protocol to prioritize vehicles on local roads over vehicles on arterials, increasing the total vehicle delay. A third theoretical example demonstrates that reservations can encourage selfish route choice leading to arbitrarily large queues. Next, we present two realistic networks taken from metropolitan planning organization data in which reservations perform worse than signals. We conclude with significantly positive results from comparing reservations and signals on the downtown Austin grid network using dynamic traffic assignment. Overall, these results indicate that network-based analyses are needed to detect adverse route choices before traffic signals can be replaced with reservation controls. In asymmetric intersections (e.g. local road-arterial intersections), reservation controls can cause several potential issues. However, in networks with more symmetric intersections such as a downtown grid, reservations have great potential to improve traffic.
Paradoxes of reservation-based intersection controls in traffic networks
Levin, Michael W. (author) / Boyles, Stephen D. (author) / Patel, Rahul (author)
Transportation Research Part A: Policy and Practice ; 90 ; 14-25
2016-05-05
12 pages
Article (Journal)
Electronic Resource
English
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